Handbook Of Evolutionary Machine Learning

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Handbook of Evolutionary Machine Learning

Wolfgang Banzhaf,Penousal Machado,Mengjie Zhang
Handbook of Evolutionary Machine Learning Book PDF

Author : Wolfgang Banzhaf,Penousal Machado,Mengjie Zhang
Publisher : Springer
Page : 0 pages
File Size : 47,8 Mb
Release : 2023-12-11
Category : Computers
ISBN : 9819938139

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Handbook of Evolutionary Machine Learning by Wolfgang Banzhaf,Penousal Machado,Mengjie Zhang Pdf

This book, written by leading international researchers of evolutionary approaches to machine learning, explores various ways evolution can address machine learning problems and improve current methods of machine learning. Topics in this book are organized into five parts. The first part introduces some fundamental concepts and overviews of evolutionary approaches to the three different classes of learning employed in machine learning. The second addresses the use of evolutionary computation as a machine learning technique describing methodologic improvements for evolutionary clustering, classification, regression, and ensemble learning. The third part explores the connection between evolution and neural networks, in particular the connection to deep learning, generative and adversarial models as well as the exciting potential of evolution with large language models. The fourth part focuses on the use of evolutionary computation for supporting machine learning methods. This includes methodological developments for evolutionary data preparation, model parametrization, design, and validation. The final part covers several chapters on applications in medicine, robotics, science, finance, and other disciplines. Readers find reviews of application areas and can discover large-scale, real-world applications of evolutionary machine learning to a variety of problem domains. This book will serve as an essential reference for researchers, postgraduate students, practitioners in industry and all those interested in evolutionary approaches to machine learning.

Handbook of Evolutionary Machine Learning

Wolfgang Banzhaf,Penousal Machado,Mengjie Zhang
Handbook of Evolutionary Machine Learning Book PDF

Author : Wolfgang Banzhaf,Penousal Machado,Mengjie Zhang
Publisher : Springer Nature
Page : 764 pages
File Size : 42,5 Mb
Release : 2023-11-01
Category : Computers
ISBN : 9789819938148

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Handbook of Evolutionary Machine Learning by Wolfgang Banzhaf,Penousal Machado,Mengjie Zhang Pdf

This book, written by leading international researchers of evolutionary approaches to machine learning, explores various ways evolution can address machine learning problems and improve current methods of machine learning. Topics in this book are organized into five parts. The first part introduces some fundamental concepts and overviews of evolutionary approaches to the three different classes of learning employed in machine learning. The second addresses the use of evolutionary computation as a machine learning technique describing methodologic improvements for evolutionary clustering, classification, regression, and ensemble learning. The third part explores the connection between evolution and neural networks, in particular the connection to deep learning, generative and adversarial models as well as the exciting potential of evolution with large language models. The fourth part focuses on the use of evolutionary computation for supporting machine learning methods. This includes methodological developments for evolutionary data preparation, model parametrization, design, and validation. The final part covers several chapters on applications in medicine, robotics, science, finance, and other disciplines. Readers find reviews of application areas and can discover large-scale, real-world applications of evolutionary machine learning to a variety of problem domains. This book will serve as an essential reference for researchers, postgraduate students, practitioners in industry and all those interested in evolutionary approaches to machine learning.

Evolutionary Deep Learning

Micheal Lanham
Evolutionary Deep Learning Book PDF

Author : Micheal Lanham
Publisher : Simon and Schuster
Page : 599 pages
File Size : 47,8 Mb
Release : 2023-10-03
Category : Computers
ISBN : 9781638352327

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Evolutionary Deep Learning by Micheal Lanham Pdf

Discover one-of-a-kind AI strategies never before seen outside of academic papers! Learn how the principles of evolutionary computation overcome deep learning’s common pitfalls and deliver adaptable model upgrades without constant manual adjustment. In Evolutionary Deep Learning you will learn how to: Solve complex design and analysis problems with evolutionary computation Tune deep learning hyperparameters with evolutionary computation (EC), genetic algorithms, and particle swarm optimization Use unsupervised learning with a deep learning autoencoder to regenerate sample data Understand the basics of reinforcement learning and the Q-Learning equation Apply Q-Learning to deep learning to produce deep reinforcement learning Optimize the loss function and network architecture of unsupervised autoencoders Make an evolutionary agent that can play an OpenAI Gym game Evolutionary Deep Learning is a guide to improving your deep learning models with AutoML enhancements based on the principles of biological evolution. This exciting new approach utilizes lesser-known AI approaches to boost performance without hours of data annotation or model hyperparameter tuning. In this one-of-a-kind guide, you’ll discover tools for optimizing everything from data collection to your network architecture. About the technology Deep learning meets evolutionary biology in this incredible book. Explore how biology-inspired algorithms and intuitions amplify the power of neural networks to solve tricky search, optimization, and control problems. Relevant, practical, and extremely interesting examples demonstrate how ancient lessons from the natural world are shaping the cutting edge of data science. About the book Evolutionary Deep Learning introduces evolutionary computation (EC) and gives you a toolbox of techniques you can apply throughout the deep learning pipeline. Discover genetic algorithms and EC approaches to network topology, generative modeling, reinforcement learning, and more! Interactive Colab notebooks give you an opportunity to experiment as you explore. What's inside Solve complex design and analysis problems with evolutionary computation Tune deep learning hyperparameters Apply Q-Learning to deep learning to produce deep reinforcement learning Optimize the loss function and network architecture of unsupervised autoencoders Make an evolutionary agent that can play an OpenAI Gym game About the reader For data scientists who know Python. About the author Micheal Lanham is a proven software and tech innovator with over 20 years of experience. Table of Contents PART 1 - GETTING STARTED 1 Introducing evolutionary deep learning 2 Introducing evolutionary computation 3 Introducing genetic algorithms with DEAP 4 More evolutionary computation with DEAP PART 2 - OPTIMIZING DEEP LEARNING 5 Automating hyperparameter optimization 6 Neuroevolution optimization 7 Evolutionary convolutional neural networks PART 3 - ADVANCED APPLICATIONS 8 Evolving autoencoders 9 Generative deep learning and evolution 10 NEAT: NeuroEvolution of Augmenting Topologies 11 Evolutionary learning with NEAT 12 Evolutionary machine learning and beyond

Handbook of Neuroevolution Through Erlang

Gene I. Sher
Handbook of Neuroevolution Through Erlang Book PDF

Author : Gene I. Sher
Publisher : Springer Science & Business Media
Page : 836 pages
File Size : 43,9 Mb
Release : 2012-11-06
Category : Computers
ISBN : 9781461444633

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Handbook of Neuroevolution Through Erlang by Gene I. Sher Pdf

Handbook of Neuroevolution Through Erlang presents both the theory behind, and the methodology of, developing a neuroevolutionary-based computational intelligence system using Erlang. With a foreword written by Joe Armstrong, this handbook offers an extensive tutorial for creating a state of the art Topology and Weight Evolving Artificial Neural Network (TWEANN) platform. In a step-by-step format, the reader is guided from a single simulated neuron to a complete system. By following these steps, the reader will be able to use novel technology to build a TWEANN system, which can be applied to Artificial Life simulation, and Forex trading. Because of Erlang’s architecture, it perfectly matches that of evolutionary and neurocomptational systems. As a programming language, it is a concurrent, message passing paradigm which allows the developers to make full use of the multi-core & multi-cpu systems. Handbook of Neuroevolution Through Erlang explains how to leverage Erlang’s features in the field of machine learning, and the system’s real world applications, ranging from algorithmic financial trading to artificial life and robotics.

Evolutionary Computation

David B. Fogel
Evolutionary Computation Book PDF

Author : David B. Fogel
Publisher : John Wiley & Sons
Page : 294 pages
File Size : 44,5 Mb
Release : 2006-01-03
Category : Technology & Engineering
ISBN : 9780471749202

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Evolutionary Computation by David B. Fogel Pdf

This Third Edition provides the latest tools and techniques that enable computers to learn The Third Edition of this internationally acclaimed publication provides the latest theory and techniques for using simulated evolution to achieve machine intelligence. As a leading advocate for evolutionary computation, the author has successfully challenged the traditional notion of artificial intelligence, which essentially programs human knowledge fact by fact, but does not have the capacity to learn or adapt as evolutionary computation does. Readers gain an understanding of the history of evolutionary computation, which provides a foundation for the author's thorough presentation of the latest theories shaping current research. Balancing theory with practice, the author provides readers with the skills they need to apply evolutionary algorithms that can solve many of today's intransigent problems by adapting to new challenges and learning from experience. Several examples are provided that demonstrate how these evolutionary algorithms learn to solve problems. In particular, the author provides a detailed example of how an algorithm is used to evolve strategies for playing chess and checkers. As readers progress through the publication, they gain an increasing appreciation and understanding of the relationship between learning and intelligence. Readers familiar with the previous editions will discover much new and revised material that brings the publication thoroughly up to date with the latest research, including the latest theories and empirical properties of evolutionary computation. The Third Edition also features new knowledge-building aids. Readers will find a host of new and revised examples. New questions at the end of each chapter enable readers to test their knowledge. Intriguing assignments that prepare readers to manage challenges in industry and research have been added to the end of each chapter as well. This is a must-have reference for professionals in computer and electrical engineering; it provides them with the very latest techniques and applications in machine intelligence. With its question sets and assignments, the publication is also recommended as a graduate-level textbook.

Evolutionary Computation

David B. Fogel
Evolutionary Computation Book PDF

Author : David B. Fogel
Publisher : Wiley-IEEE Press
Page : 664 pages
File Size : 44,7 Mb
Release : 1998-05-15
Category : Computers
ISBN : UCSD:31822025962747

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Evolutionary Computation by David B. Fogel Pdf

Although evolutionary computation has only been a popular topic for the last 20 years, it actually has antecedents back in the '50s. This is the first text to present the most significant and historic papers on evolutionary computation ranging from the '50s to the early '90s. Features a comprehensive bibliography of the available literature in the field.

Introduction to Evolutionary Computing

Agoston E. Eiben,J.E. Smith
Introduction to Evolutionary Computing Book PDF

Author : Agoston E. Eiben,J.E. Smith
Publisher : Springer Science & Business Media
Page : 307 pages
File Size : 43,8 Mb
Release : 2013-03-14
Category : Computers
ISBN : 9783662050941

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Introduction to Evolutionary Computing by Agoston E. Eiben,J.E. Smith Pdf

The first complete overview of evolutionary computing, the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. The text is aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to apply evolutionary computing to a particular problem or within a given application area. The book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.

Handbook of Evolutionary Computation

Thomas Bäck
Handbook of Evolutionary Computation Book PDF

Author : Thomas Bäck
Publisher : Inst of Physics Pub Incorporated
Page : 988 pages
File Size : 45,8 Mb
Release : 1997
Category : Computers
ISBN : 0750303921

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Handbook of Evolutionary Computation by Thomas Bäck Pdf

Many scientists and engineers now use the paradigms of evolutionary computation (genetic algorithms, evolution strategies, evolutionary programming, genetic programming, classifier systems, and combinations or hybrids thereof) to tackle problems that are either intractable or unrealistically time consuming to solve through traditional computational strategies. Recently there have been vigorous initiatives to promote cross-fertilization between the EC paradigms, and also to combine these paradigms with other approaches such as neural networks to create hybrid systems with enhanced capabilities. To address the need for speedy dissemination of new ideas in these fields, and also to assist in cross-disciplinary communications and understanding, Oxford University Press and the Institute of Physics have joined forces to create a major reference publication devoted to EC fundamentals, models, algorithms and applications. This work is intended to become the standard reference resource for the evolutionary computation community. The Handbook of Evolutionary Computation will be available in loose-leaf print form, as well as in an electronic version that combines both CD-ROM and on-line (World Wide Web) access to its contents. Regularly published supplements will be available on a subscription basis.

Handbook On Computer Learning And Intelligence (In 2 Volumes)

Plamen Parvanov Angelov
Handbook On Computer Learning And Intelligence In 2 Volumes Book PDF

Author : Plamen Parvanov Angelov
Publisher : World Scientific
Page : 1057 pages
File Size : 51,5 Mb
Release : 2022-06-29
Category : Computers
ISBN : 9789811247330

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Handbook On Computer Learning And Intelligence (In 2 Volumes) by Plamen Parvanov Angelov Pdf

The Handbook on Computer Learning and Intelligence is a second edition which aims to be a one-stop-shop for the various aspects of the broad research area of computer learning and intelligence. This field of research evolved so much in the last five years that it necessitates this new edition of the earlier Handbook on Computational Intelligence.This two-volume handbook is divided into five parts. Volume 1 covers Explainable AI and Supervised Learning. Volume 2 covers three parts: Deep Learning, Intelligent Control, and Evolutionary Computation. The chapters detail the theory, methodology and applications of computer learning and intelligence, and are authored by some of the leading experts in the respective areas. The fifteen core chapters of the previous edition have been written and significantly refreshed by the same authors. Parts of the handbook have evolved to keep pace with the latest developments in computational intelligence in the areas that span across Machine Learning and Artificial Intelligence. The Handbook remains dedicated to applications and engineering-orientated aspects of these areas over abstract theories.Related Link(s)

The Practical Handbook of Genetic Algorithms

Lance D. Chambers
The Practical Handbook of Genetic Algorithms Book PDF

Author : Lance D. Chambers
Publisher : CRC Press
Page : 503 pages
File Size : 53,7 Mb
Release : 2019-09-17
Category : Mathematics
ISBN : 9780429525568

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The Practical Handbook of Genetic Algorithms by Lance D. Chambers Pdf

The mathematics employed by genetic algorithms (GAs)are among the most exciting discoveries of the last few decades. But what exactly is a genetic algorithm? A genetic algorithm is a problem-solving method that uses genetics as its model of problem solving. It applies the rules of reproduction, gene crossover, and mutation to pseudo-organism

Evolutionary Computation 1

Thomas Baeck,D.B Fogel,Z Michalewicz
Evolutionary Computation 1 Book PDF

Author : Thomas Baeck,D.B Fogel,Z Michalewicz
Publisher : CRC Press
Page : 374 pages
File Size : 40,6 Mb
Release : 2018-10-03
Category : Mathematics
ISBN : 9781351989428

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Evolutionary Computation 1 by Thomas Baeck,D.B Fogel,Z Michalewicz Pdf

The field of evolutionary computation is expanding dramatically, fueled by the vast investment that reflects the value of applying its techniques. Culling material from the Handbook of Evolutionary Computation, Evolutionary Computation 1: Basic Algorithms and Operators contains up-to-date information on algorithms and operators used in evolutionary computing. This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming. It is intended to be used by individual researchers, teachers, and students working and studying in this expanding field.

Evolutionary Machine Learning Techniques

Seyedali Mirjalili,Hossam Faris,Ibrahim Aljarah
Evolutionary Machine Learning Techniques Book PDF

Author : Seyedali Mirjalili,Hossam Faris,Ibrahim Aljarah
Publisher : Springer Nature
Page : 286 pages
File Size : 55,8 Mb
Release : 2019-11-11
Category : Technology & Engineering
ISBN : 9789813299900

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Evolutionary Machine Learning Techniques by Seyedali Mirjalili,Hossam Faris,Ibrahim Aljarah Pdf

This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm, dragonfly algorithm, salp swarm algorithm, multi-verse optimizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.

Data-Driven Evolutionary Optimization

Yaochu Jin,Handing Wang,Chaoli Sun
Data Driven Evolutionary Optimization Book PDF

Author : Yaochu Jin,Handing Wang,Chaoli Sun
Publisher : Springer Nature
Page : 393 pages
File Size : 54,7 Mb
Release : 2021-06-28
Category : Computers
ISBN : 9783030746407

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Data-Driven Evolutionary Optimization by Yaochu Jin,Handing Wang,Chaoli Sun Pdf

Intended for researchers and practitioners alike, this book covers carefully selected yet broad topics in optimization, machine learning, and metaheuristics. Written by world-leading academic researchers who are extremely experienced in industrial applications, this self-contained book is the first of its kind that provides comprehensive background knowledge, particularly practical guidelines, and state-of-the-art techniques. New algorithms are carefully explained, further elaborated with pseudocode or flowcharts, and full working source code is made freely available. This is followed by a presentation of a variety of data-driven single- and multi-objective optimization algorithms that seamlessly integrate modern machine learning such as deep learning and transfer learning with evolutionary and swarm optimization algorithms. Applications of data-driven optimization ranging from aerodynamic design, optimization of industrial processes, to deep neural architecture search are included.

Handbook of Genetic Programming Applications

Amir H. Gandomi,Amir H. Alavi,Conor Ryan
Handbook of Genetic Programming Applications Book PDF

Author : Amir H. Gandomi,Amir H. Alavi,Conor Ryan
Publisher : Springer
Page : 593 pages
File Size : 45,5 Mb
Release : 2015-11-06
Category : Computers
ISBN : 9783319208831

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Handbook of Genetic Programming Applications by Amir H. Gandomi,Amir H. Alavi,Conor Ryan Pdf

This contributed volume, written by leading international researchers, reviews the latest developments of genetic programming (GP) and its key applications in solving current real world problems, such as energy conversion and management, financial analysis, engineering modeling and design, and software engineering, to name a few. Inspired by natural evolution, the use of GP has expanded significantly in the last decade in almost every area of science and engineering. Exploring applications in a variety of fields, the information in this volume can help optimize computer programs throughout the sciences. Taking a hands-on approach, this book provides an invaluable reference to practitioners, providing the necessary details required for a successful application of GP and its branches to challenging problems ranging from drought prediction to trading volatility. It also demonstrates the evolution of GP through major developments in GP studies and applications. It is suitable for advanced students who wish to use relevant book chapters as a basis to pursue further research in these areas, as well as experienced practitioners looking to apply GP to new areas. The book also offers valuable supplementary material for design courses and computation in engineering.

A Field Guide to Genetic Programming

Anonim
A Field Guide to Genetic Programming Book PDF

Author : Anonim
Publisher : Lulu.com
Page : 252 pages
File Size : 44,5 Mb
Release : 2008
Category : Computers
ISBN : 9781409200734

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A Field Guide to Genetic Programming by Anonim Pdf

Genetic programming (GP) is a systematic, domain-independent method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. Using ideas from natural evolution, GP starts from an ooze of random computer programs, and progressively refines them through processes of mutation and sexual recombination, until high-fitness solutions emerge. All this without the user having to know or specify the form or structure of solutions in advance. GP has generated a plethora of human-competitive results and applications, including novel scientific discoveries and patentable inventions. This unique overview of this exciting technique is written by three of the most active scientists in GP. See www.gp-field-guide.org.uk for more information on the book.